Entropy-Based Envelope Generator for Pipe-Strike Pulse Detection
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Solution Overview
Problem
Existing methods for monitoring underground pipelines face challenges in distinguishing noise pulses from background noise, leading to false detections due to high sensitivity of acoustic sensors, which are prone to noise from sources like traffic, pedestrians, and weather conditions.
Innovation Solution
A method utilizing an entropy-based envelope generator to convert sensor signals into envelope signals, integrating them over consecutive periods, calculating ratios, and setting flags to differentiate noise pulses from background noise, specifically effective for Poisson-, Erlang-, and log-normal-distributed pulses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic sensors with high sensitivity are used to monitor underground pipelines, then detection capability is improved, but false alarms increase due to background noise from traffic, pedestrians, and weather conditions
Solution Approach 1:
The signal processing is divided into multiple integration periods, with each period independently analyzing the envelope signal. This segmentation allows the system to distinguish between transient noise pulses and sustained background noise, improving reliability while maintaining detection capability.
Solution Approach 2:
The system uses periodic integration over consecutive time periods to analyze the signal. By comparing ratios across multiple periods and setting flags based on threshold comparisons, the system can identify genuine pipeline strikes while filtering out periodic background noise patterns.
2Measurement precision
If acoustic sensors are used to detect pipeline impacts, then impact detection capability is improved, but noise from various sources masks the signal of interest
Solution Approach 1:
The system extracts the envelope signal from the raw acoustic sensor output using an entropy-based envelope generator. This extraction isolates the relevant signal characteristics from the masking background noise, enabling impact detection even when the signal is buried in noise.
Solution Approach 2:
The system transforms the signal from the time domain to the envelope domain by calculating the entropy-based envelope. This parameter transformation changes the signal representation, making impact events distinguishable from background noise through ratio comparisons across integration periods.
Data Source
AI summary
A method for discriminating a noise pulse from a background noise in which a signal of interest is converted to an envelope signal using an entropy-based envelope generator, which envelope signal is then integrated over a plurality of consecutive integrative periods, producing an integrated envelope signal for each of the integration periods. The ratio of the envelope signal at the end of each of the integration periods corresponding to each corresponding said integrated envelope signal is determined and compared with a predetermined threshold signal for each of the integration periods, resulting in a comparison value. The integration period in which the comparison value exceeds the predetermined threshold signal and which is preceded by two integration periods in which the comparison value does not exceed the threshold value represents the point in time at which the noise pulse is detected.